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This study aims to estimate attenuation characteristics of the central Himalayan region of India concerning various strong-motion parameters such as Kappa value (κ) and site effects. We have tried to elaborate on the regional structural heterogeneities and their implications towards the seismic hazard assessment of the study region. A total of 81 earthquakes recorded at 50 stations situated in the central Himalayan region of India are used for the purpose. The particular focus is kept on Kappa value, which shows variability from 0.03 s to 0.095 s, inferring the higher values obtained in plains with deep sediment accumulations proving high-frequency energy dissipation and stiff-soil/rocky sites exhibit comparatively limited attenuation accordingly. To substantiate these results various attenuation parameters such as coda wave quality factor (Qc), intrinsic attenuation parameter (Qi), and scattering attenuation parameter (Qs), have been estimated for two regions in the central seismic gap Himalayan region of India employing the single backscattering model and Wennerberg formulation. The estimated values of Qc, Qi, and Qs are found to be highly dependent on frequency in the frequency range 1.5–24 Hz for both the regions. The average frequency-dependent relationships ( Q = Q 0 f η ) estimated for both regions are Q c = 158 f 1.18 and Q c = 194 f 1.2 , respectively. The low value of Q0 shows that the region is highly heterogeneous while the higher value of η indicates higher seismicity in the area. It is also found that intrinsic attenuation is predominant over the scattering attenuation, envisaging the behavior of the wave attenuation through the absorption within the granitic layer at shallow depths. At lower frequencies, Qc values are found close to Qs values, which is in agreement with the theoretical measurements suggesting the presence of complex crustal heterogeneities beneath the region affecting the propagation of seismic waves experiencing considerable decay of energy through scattering. To confirm the aggregate attenuation on the stations, the site characteristics are also determined for examining the behavior of the amplification as the ground motion is comprised of the combined effect of the source, path, and site. The sites are amplified at a predominant frequency (fpeak) in between 1.5 to 10 Hz for the central Himalayan region. The different attenuation and amplification parameters like kappa, Q, and site effects can be utilized for detailed seismic hazard analysis (based on ground motion prediction equations) of the area as this region is of great importance from a socio-economic point of view. [ABSTRACT FROM AUTHOR]

Ambient noise interferometry is a powerful technique to continuously measuring crustal seismic velocity changes (dv/v) and studying crustal behaviors over time. However, the interpretation of such dv/v variations is not straightforward since multiple causes including internal (tectonic/magmatic) processes of the crust and external (environmental) factors could both affect dv/v simultaneously. To differentiate the interplay between the internal and external processes in dv/v variations is an essential step toward accurate crustal monitoring. In this study, we apply the single‐station cross‐component (SC) method to 15 selected stations from the Broadband Array in Taiwan for Seismology (BATS) to investigate the temporal evolution of crustal seismic velocities across Taiwan. We process the continuous BATS seismic recording from 1998 to 2019, construct the daily SC correlation functions, and compute dv/v values by the stretching technique in a frequency band of 0.1–0.9 Hz. We observe both strong annual dv/v variations and co‐seismic velocity drops associated with regional moderate‐to‐large earthquakes. Systematic spectral and time‐series analyses with the weather data suggest that the rainfall‐induced pore‐pressure change plays a predominant role in driving the dv/v seasonality, reflecting a diffusion process from meteoric water into shallow crust. The effects of other factors are relatively local and secondary. We also demonstrate how understanding and correcting rainfall effects could critically improve the resolution and accuracy of internal crustal damage related to earthquakes. Plain Language Summary: The measured wave speeds from small ground motions such as ocean, wind, traffic, etc help us to understand changes in subterranean regions. The causes of the medium changes are multifold such as the fault zone damage by earthquakes (internal) or groundwater rise by rainfall (external). To discriminate the causes it is important to use weak ground motions for monitoring internal medium changes. For this purpose, we collect and study 20 years of ground motion data from 15 seismic stations distributed across Taiwan. We measure the propagation wave speed of weak ground motions and find earthquake‐related changes and strong seasonal changes at most stations. By analyzing and comparing wave speed changes with weather data (e.g., rainfall, temperature, air pressure, and wind speed), we find that rainfall varying groundwater level and the subterranean pore pressure best fit the seasonal wave speed changes in both space and time. After removing this rainfall‐related signals, we can estimate more precisely the extent of earthquake‐related underground damages that may not be obvious or completely masked by the strong seasonal changes. Key Points: We observe both coseismic dv/v drops and strong seasonal dv/v variations through a 20‐year systematic analysis in TaiwanThe rainfall‐induced pore pressure change is likely the primary control of the seasonal dv/v variations in the crustEvaluating the environmental influences on dv/v allows us to isolate crustal damage related to earthquakes [ABSTRACT FROM AUTHOR]

Earthquake early warning system uses high-speed computer network to transmit earthquake information to population center ahead of the arrival of destructive earthquake waves. This short (10 s of seconds) lead time will allow emergency responses such as turning off gas pipeline valves to be activated to mitigate potential disaster and casualties. However, the excessive false alarm rate of such a system imposes heavy cost in terms of loss of services, undue panics, and diminishing credibility of such a warning system. At the current, the decision algorithm to issue an early warning of the onset of an earthquake is often based on empirically chosen features and heuristically set thresholds and suffers from excessive false alarm rate. In this paper, we experimented with three advanced machine learning algorithms, namely, $K$ -nearest neighbor (KNN), classification tree, and support vector machine (SVM) and compared their performance against a traditional criterion-based method. Using the seismic data collected by an experimental strong motion detection network in Taiwan for these experiments, we observed that the machine learning algorithms exhibit higher detection accuracy with much reduced false alarm rate. [ABSTRACT FROM AUTHOR]

Abstract: We investigate the spatial and temporal variations of b-values before twenty-three earthquakes with M L ≥6.0 in the Taiwan region from 1999 to 2009. We estimate the spatial distribution of b-values within a one-year period before the occurrence of investigated earthquakes. It shows that the epicenters of those earthquakes are located predominately in the regions with low b-values relative to the entire study area. In terms of temporal evolutions, the b-values are slightly lower during the year prior to the investigated earthquakes in comparison to the periods two to five years earlier. We propose that these anomalies may offer spatiotemporal constraints for the earthquake forecasting in Taiwan in the future. [Copyright &y& Elsevier]

Abstract: The use of characteristic period τc and peak displacement amplitude Pd of the initial P wave in earthquake early warning (EEW) was proposed by Wu and Kanamori . Here we apply this approach to strong-motion records from a building sensor array installed in Taitung County, Taiwan. This building was damaged during the 2006 Mw =6.1 Taitung earthquake with a peak ground velocity (PGV) of up to 38.4cm/s at an epicentral distance of 14.5km. According to our analysis, the peak displacement amplitude Pd is a better indicator for the destructiveness of an earthquake than τc because τc is more sensitive to the signal-to-noise ratio (SNR) than Pd. In accordance with previous studies, only the structurally damaging Taitung earthquake generated a Pd value larger than 0.5cm (a threshold for identifying damaging events). Using Pd as an indicator for destructive earthquakes does not lead to missing or false alarms for EEW purposes. [ABSTRACT FROM AUTHOR]

It is understood that sample size could be an issue in earthquake statistical studies, causing the best estimate being too deterministic or less representative derived from limited statistics from observation. Like many Bayesian analyses and estimates, this study shows another novel application of the Bayesian approach to earthquake engineering, using prior data to help compensate the limited observation for the target problem to estimate the magnitude of the recurring Meishan earthquake in central Taiwan. With the Bayesian algorithms developed, the Bayesian analysis suggests that the next major event induced by the Meishan fault in central Taiwan should be in M w 6.44±0.33, based on one magnitude observation of M w 6.4 from the last event, along with the prior data including fault length of 14 km, rupture width of 15 km, rupture area of 216 km 2 , average displacement of 0.7 m, slip rate of 6 mm/yr, and five earthquake empirical models. [ABSTRACT FROM AUTHOR]

Abstract: The 900-km-long Red River shear zone (RRSZ) lends a compelling support to the continental extrusion model for the tectonic evolution of southeastern Asia, but has been challenged by many of views, as some new records mainly from northern Vietnam, suspecting the dimensions of RRSZ neither in depth nor in displacement are as large as we expected before. However, compared to the northwestern half of the RRSZ in Yunnan province better studied by many fields, the southeastern half in northern Vietnam is relatively poorly constrained by seismic study, due to insufficient stations and data in the past. This study, using a newly deployed portable broadband seismic network, obtained the first local seismic tomography with a stepwise inversion using P and Pn phases. Surface geology, major structures, and rock properties are well correlated and identified in our model, suggesting the RRSZ is a lithospheric structure at least penetrating to the uppermost mantle with mantle thermal anomalies. In general, the crust of northern Vietnam appears to be weak and sits on a relatively hot uppermost mantle, showing a long and complex thermo tectonic history. A mid-lower crustal segmentation of RRSZ is also proposed to compromise the discrepancies recently observed between Yunnan province and northern Vietnam. [Copyright &y& Elsevier]

Abstract: Two recent catastrophic earthquakes that struck the Marmara Region on 17 August 1999 (Mw =7.4) and 12 November 1999 (Mw =7.2) caused major concern about future earthquake occurrences in Istanbul and the Marmara Region. As a result of the preparations for an expected earthquake may occur around Istanbul region, an earthquake early warning system has been established in 2002 with a simple and robust algorithm, based on the exceedance of specified thresholds of time domain amplitudes and the cumulative absolute velocity (CAV) levels (Erdik et al., 2003 ). In order to improve the capability of Istanbul earthquake early warning system (IEEWS) for giving early warning of a damaging earthquake in the Marmara Region, we explored an alternative approach with the use of a period parameter (τc ) and a high-pass filtered vertical displacement amplitude parameter (Pd) from the initial 3s of the P waveforms as proposed by Kanamori (2005) and Wu and Kanamori (2005) . The empirical relationships both between τc and moment magnitude (Mw ), and between Pd and peak ground velocity (PGV) for the Marmara Region are presented. These relationships can be used to detect a damaging earthquake within seconds after the arrival of P waves, and can provide on-site warning in the Marmara Region. [ABSTRACT FROM AUTHOR]

Earthquake early warning (EEW) plays an important role in earthquake disaster mitigation. There are two types of EEW system, regional and on-site. On-site EEW systems analyze initial part of the seismic waves from the P-waves to predict later ground motion from the S-waves and surface waves. In recent years, an on-site EEW method based on fixed peak displacement (Pd) threshold is developed. Although the method consistently provides effective warnings in Taiwan, several studies suggest that its strong filter dependence might introduce extra biases to the system. Also, the fixed Pd threshold suffers from the inevitable trade-off between a false alarm and a missed alarm. In order to overcome the abovementioned problems of fixed Pd threshold method, we utilize techniques in machine learning and develop a new method of on-site early warning. Owing to the property that convoluted-neural-network (CNN) will automatic sampling on different frequencies, the unfiltered seismic signal itself is sufficient to derive a warning threshold. Also, multi-layered neural-network is capable of forming a complex non-linear threshold to reduce both the false alarms and missed alarms. As an example, we collect 21 medium to large inland earthquakes in Taiwan. We compare the performance between the proposed method and the fixed Pd threshold method. The result shows that the proposed method outperforms in both false alarm rate (0.01 percent) and missed alarm rate (30 percent). The proposed method can provide not only significant improvements for on-site EEW but also a window into the initial P-waves. Studying the trained models might even reveal the hidden indicators inside the initial P-waves.Keywords: earthquake disaster mitigation, on-site type earthquake early warning, machine learning [ABSTRACT FROM AUTHOR]

Recent studies have shown that structural damage exhibits stronger correlations with cumulative absolute velocity (CAV) than other ground motion intensity measures (e.g., PGA). This paper presents a CAV site-effect assessment for the Taipei areas for the first time. The study was based on more than 1200 strong-motion data from 47 major earthquakes that had occurred around Taiwan. The results show that the site effects are more conspicuous in the western Taipei than the eastern areas, and it is also obvious that the site effect is strong in locations close to the rims of the basin, where seismic waves could be easily reflected, refracted and superimposed. Subsequently, a map showing the areas in Taipei subject to severe CAV amplification and/or high variability was developed for site-effect microzonation for the study area, on the basis of CAV that was considered better correlated with structural damage under earthquake condition. [ABSTRACT FROM AUTHOR]

In this paper, we study (1) the spatial anomalies and (2) the temporal anomalies of soil gas in northern Taiwan. The spatial anomalies of soil gas are related to tectonic faults, while the temporal anomalies of soil gas are associated with pre-earthquake activities. Detailed soil gas sampling was systematically performed, and the analysis of the collected gas species shows that high helium and nitrogen concentrations appear in samples from specific sites, which coincide with the structural setting of the area studied. This analysis indicates the possibility of using these soil gases to determine fault zones in the studied area. Based on the soil gas data, a station (Tapingti) for automatic soil gas monitoring was constructed on an appropriate site at the fault zone. Some anomalous high radon concentrations at certain times can be identified from the dataset, which was generated by the continuous monitoring of soil gas for over a year. Notably, many of these anomalies were observed several hours to a few days before the earthquakes (M L > 3) that occurred in northern Taiwan. By combining the information of epicenters and fault plane solutions of these earthquakes, we find that the shallow earthquakes (<15 km) were mainly strike-slip and normal-type earthquakes, and concentrated within a distance of 30 km to the monitoring site (Group A). The deep earthquakes (>20 km) were mainly thrust-type earthquakes and distributed in greater distances (>45 km) east of the monitoring site (Group B). Such focal mechanisms of earthquakes suggest an extensional and compressional structural domain in the continental crust for Group A and Group B earthquakes, respectively. It is suggested that the pre-earthquake activities associated with the seismicity of Group B may be transmitted along the major decollement in the region below the Tapingti station, leading to the observed soil gas enhancements. [ABSTRACT FROM AUTHOR]